Abdullah Mueen

5 Slides Demo

Primitives for Time Series Data Mining

▪ Time series motifs

▪ Time series shapelets

▪ Time series join

0 2000 4000 6000 8000 100000

102030

0 100 200 300 400 500 600 700 800

3/27/1996 2/24/1998 1/25/2000 12/25/2001 11/25/2003 10/25/2005 9/25/2007 8/25/2009 7/26/2011 6/26/2013

-4

-3

-2

-1

0

1

2

3

4

Indian Rupee (INR)Singapore Dollar (SGD)

113 days

Is P within τ?

yes no P

JoinMotif

Shapelet

Phonetic Time Series Mining

▪ Phoneme Classification

▪ Accent Classification

Obstruent

Fricative

S SH

Affricate

CHgasser/G AE S ER/

unattached/AH N AH T AE CH T/

appreciable/AH P R IY SH AH B AH L/

cliched/K L IY SH EY D/

DTW label MFCC labelDual Domain label

Sonorants

Vowel

EY IY

Semi-vowel

DTW label MFCC labelDual Domain label

savagely/S AE V IH JH L IY /

deactivate/D IY AE K T IH V EY T /

valueless/V AE L Y UW L AH S/

philosophically/F IH L AH S AA F IH K L IY /

Mining Heterogeneous Online Reviews

▪ Identifying spamming owners

▪ Combining multi-source information

▪ Analytical tool for hosting sites

Mining Motion Data

▪ Classifying motion category

▪ Invariant to plane and length of motion

0 10 20 30 40 50 60 70-4

-2

0

2

0 10 20 30 40 50 60 70-4

-2

0

2

Walking on Carpet (Soft)

Walking on Cement (Hard)

0 10 20 30 40 50 60 70-4

-2

0

2

4

S1S2

1-NN 69.55%

1-NN DTW 72.55%

1-NN DTW S-C 69.55%

Shapelet (S1) 93.34%

Shapelets (S1 and S2 )

96.34%

x 104

ABC

EF

A AA BCC

DDDDDD EEFF

0 0.5 1 1.5 2 2.5 3

0/20/22/4

0/30/40/2

Hand

Legxyz

xyz

Contextual Change Detection

0 10 20 30 40 50 60 70 80 90 100-20

-15

-10

-5

0

5

10

15

0 10 20 30 40 50 60 70 80 90 100-20

-15

-10

-5

0

5

0 10 20 30 40 50 60 70 80 90 100-20

-15

-10

-5

0

5

10

15

20

Disbanding

Formation

-20

-15

-10

-5

0

5

0 10 20 30 40 50 60 70 80 90 100

25-May-2007 25-May-2008 25-May-2009 25-May-2010 25-May-2011 25-May-2012

0.05

0.15

0.25

0.35

Contextual Change